Composite wavelet representations for reconstruction of missing data

被引：3
|
作者：
Czaja, Wojciech [1 ]
Dobrosotskaya, Julia [1 ]
Manning, Benjamin [1 ]
机构：
[1] Univ Maryland, Dept Math, College Pk, MD 20742 USA
来源：
INDEPENDENT COMPONENT ANALYSES, COMPRESSIVE SAMPLING, WAVELETS, NEURAL NET, BIOSYSTEMS, AND NANOENGINEERING XI | 2013年 / 8750卷
关键词：
Composite wavelets; variational inpainting; shearlets; NOISE REMOVAL; IMAGE;
D O I：
10.1117/12.2019219
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
We shall introduce a novel methodology for data reconstruction and recovery, based on composite wavelet representations. These representations include shearlets and crystallographic wavelets, among others, and they allow for an increased directional sensitivity in comparison with the standard multiscale techniques. Our new approach allows us to recover missing data, due to sparsity of composite wavelet representations, especially when compared to inpainting algorithms induced by traditional wavelet representations, and also due to the flexibility of our variational approach.
引用
收藏
页数：14
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